FM / torch

/usr/local/lib64/python3.6/site-packages/torch/

/usr/local/lib64/python3.6/site-packages/torch

Name	Size	Mode	Actions
ao/	-	0755	rm
autograd/	-	0755	rm
backends/	-	0755	rm
bin/	-	0755	rm
contrib/	-	0755	rm
cpu/	-	0755	rm
cuda/	-	0755	rm
distributed/	-	0755	rm
distributions/	-	0755	rm
fft/	-	0755	rm
for_onnx/	-	0755	rm
futures/	-	0755	rm
fx/	-	0755	rm
include/	-	0755	rm
jit/	-	0755	rm
lib/	-	0755	rm
linalg/	-	0755	rm
multiprocessing/	-	0755	rm
nn/	-	0755	rm
onnx/	-	0755	rm
optim/	-	0755	rm
package/	-	0755	rm
profiler/	-	0755	rm
quantization/	-	0755	rm
share/	-	0755	rm
sparse/	-	0755	rm
special/	-	0755	rm
testing/	-	0755	rm
utils/	-	0755	rm
_C/	-	0755	rm
__pycache__/	-	0755	rm
autocast_mode.py	9663	0644	edit dl rm
functional.py	71257	0644	edit dl rm
hub.py	23371	0644	edit dl rm
overrides.py	84146	0644	edit dl rm
py.typed	0	0644	edit dl rm
quasirandom.py	7489	0644	edit dl rm
random.py	4828	0644	edit dl rm
serialization.py	36544	0644	edit dl rm
storage.py	5762	0644	edit dl rm
torch_version.py	3468	0644	edit dl rm
types.py	1552	0644	edit dl rm
version.py	125	0644	edit dl rm
_appdirs.py	26245	0644	edit dl rm
_C.cpython-36m-x86_64-linux-gnu.so	29296	0755	edit dl rm
_classes.py	1717	0644	edit dl rm
_deploy.py	3100	0644	edit dl rm
_dl.cpython-36m-x86_64-linux-gnu.so	29832	0755	edit dl rm
_jit_internal.py	46910	0644	edit dl rm
_linalg_utils.py	2373	0644	edit dl rm
_lobpcg.py	44076	0644	edit dl rm
_lowrank.py	11031	0644	edit dl rm
_namedtensor_internals.py	5351	0644	edit dl rm
_ops.py	4457	0644	edit dl rm
_python_dispatcher.py	7011	0644	edit dl rm
_six.py	1858	0644	edit dl rm
_sources.py	3882	0644	edit dl rm
_storage_docs.py	1298	0644	edit dl rm
_tensor.py	50854	0644	edit dl rm
_tensor_docs.py	113474	0644	edit dl rm
_tensor_str.py	18091	0644	edit dl rm
_torch_docs.py	364678	0644	edit dl rm
_utils.py	21617	0644	edit dl rm
_utils_internal.py	1687	0644	edit dl rm
_VF.py	656	0644	edit dl rm
_vmap_internals.py	13219	0644	edit dl rm
__config__.py	551	0644	edit dl rm
__future__.py	813	0644	edit dl rm
__init__.py	31199	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/torch/_namedtensor_internals.py (5351B)

from collections import OrderedDict

"""
This file contains helper functions that implement experimental functionality
for named tensors in python. All of these are experimental, unstable, and
subject to change or deletion.
"""

def check_serializing_named_tensor(tensor):
    if tensor.has_names():
        raise RuntimeError(
            "NYI: Named tensors don't support serialization. Please drop "
            "names via `tensor = tensor.rename(None)` before serialization.")

def build_dim_map(tensor):
    """Returns a map of { dim: dim_name } where dim is a name if the dim is named
    and the dim index otherwise."""
    return OrderedDict([(idx if name is None else name, name)
                        for idx, name in enumerate(tensor.names)])

def unzip_namedshape(namedshape):
    if isinstance(namedshape, OrderedDict):
        namedshape = namedshape.items()
    if not hasattr(namedshape, '__iter__') and not isinstance(namedshape, tuple):
        raise RuntimeError(
            'Expected namedshape to be OrderedDict or iterable of tuples, got: {}'
            .format(type(namedshape)))
    if len(namedshape) == 0:
        raise RuntimeError('Expected namedshape to non-empty.')
    return zip(*namedshape)

def namer_api_name(inplace):
    if inplace:
        return 'rename_'
    else:
        return 'rename'

def is_ellipsis(item):
    return item == Ellipsis or item == '...'

def single_ellipsis_index(names, fn_name):
    ellipsis_indices = [i for i, name in enumerate(names) if is_ellipsis(name)]
    if len(ellipsis_indices) >= 2:
        raise RuntimeError('{}: More than one Ellipsis (\'...\') found in names ('
                           '{}). This function supports up to one Ellipsis.'
                           .format(fn_name, names))
    if len(ellipsis_indices) == 1:
        return ellipsis_indices[0]
    return None

def expand_single_ellipsis(numel_pre_glob, numel_post_glob, names):
    return names[numel_pre_glob:len(names) - numel_post_glob]

def replace_ellipsis_by_position(ellipsis_idx, names, tensor_names):
    globbed_names = expand_single_ellipsis(ellipsis_idx, len(names) - ellipsis_idx - 1, tensor_names)
    return names[:ellipsis_idx] + globbed_names + names[ellipsis_idx + 1:]

def resolve_ellipsis(names, tensor_names, fn_name):
    """
    Expands ... inside `names` to be equal to a list of names from `tensor_names`.
    """
    ellipsis_idx = single_ellipsis_index(names, fn_name)
    if ellipsis_idx is None:
        return names
    return replace_ellipsis_by_position(ellipsis_idx, names, tensor_names)

def update_names_with_list(tensor, names, inplace):
    # Special case for tensor.rename(None)
    if len(names) == 1 and names[0] is None:
        return tensor._update_names(None, inplace)

return tensor._update_names(
        resolve_ellipsis(names, tensor.names, namer_api_name(inplace)), inplace)

def update_names_with_mapping(tensor, rename_map, inplace):
    dim_map = build_dim_map(tensor)
    for old_dim in rename_map.keys():
        new_dim = rename_map[old_dim]
        if old_dim in dim_map.keys():
            dim_map[old_dim] = new_dim
        else:
            raise RuntimeError(('{api_name}: Tried to rename dim \'{old_dim}\' to dim '
                                '{new_dim} in Tensor[{dims}] but dim \'{old_dim}\' does not exist')
                               .format(old_dim=old_dim, new_dim=new_dim, dims=tensor.names,
                                       api_name=namer_api_name(inplace)))
    return tensor._update_names(tuple(dim_map.values()), inplace)

def update_names(tensor, names, rename_map, inplace):
    """There are two usages:

tensor.rename(*names) returns a view on tensor with named dims `names`.
    `names` must be of length `tensor.dim()`; otherwise, if '...' is in `names`,
    then it is expanded greedily to be equal to the corresponding names from
    `tensor.names`.

For example,
    ```
    >>> x = torch.empty(2, 3, 5, 7, names=('N', 'C', 'H', 'W'))
    >>> x.rename('...', 'height', 'width').names
    ('N', 'C', 'height', 'width')

>>> x.rename('batch', '...', 'width').names
    ('batch', 'C', 'H', 'width')
    ```

tensor.rename(**rename_map) returns a view on tensor that has rename dims
        as specified in the mapping `rename_map`.

For example,
    ```
    >>> x = torch.empty(2, 3, 5, 7, names=('N', 'C', 'H', 'W'))
    >>> x.rename(W='width', H='height').names
    ('N', 'C', 'height', 'width')
    ```

Finally, tensor.rename has an in-place version called tensor.rename_.
    """
    has_names = len(names) > 0
    has_rename_pairs = bool(rename_map)
    if has_names and has_rename_pairs:
        raise RuntimeError('{api_name}: This function takes either positional '
                           'args or keyword args, but not both. Use tensor.{api_name}(*names) '
                           'to name dims and tensor.{api_name}(**rename_map) to rename '
                           'dims.'.format(api_name=namer_api_name(inplace)))

# Special case for tensor.rename(*[]), which is valid for a 0 dim tensor.
    if not has_names and not has_rename_pairs:
        return update_names_with_list(tensor, names, inplace)

if has_names:
        return update_names_with_list(tensor, names, inplace)
    return update_names_with_mapping(tensor, rename_map, inplace)

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